A new tool for converting food frequency questionnaire data into nutrient and food group values: FETA research methods and availability.

BMJ OPEN(2014)

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摘要
Objectives To describe the research methods for the development of a new open source, cross-platform tool which processes data from the European Prospective Investigation into Cancer and Nutrition Norfolk Food Frequency Questionnaire (EPIC-Norfolk FFQ). A further aim was to compare nutrient and food group values derived from the current tool (FETA, FFQ EPIC Tool for Analysis) with the previously validated but less accessible tool, CAFe (Compositional Analyses from Frequency Estimates). The effect of text matching on intake data was also investigated. Design Cross-sectional analysis of a prospective cohort study-EPIC-Norfolk. Setting East England population (city of Norwich and its surrounding small towns and rural areas). Participants Complete FFQ data from 11 250 men and 13 602 women (mean age 59 years; range 40-79 years). Outcome measures Nutrient and food group intakes derived from FETA and CAFe analyses of EPIC-Norfolk FFQ data. Results Nutrient outputs from FETA and CAFe were similar; mean (SD) energy intake from FETA was 9222 kJ (2633) in men, 8113 kJ (2296) in women, compared with CAFe intakes of 9175 kJ (2630) in men, 8091 kJ (2298) in women. The majority of differences resulted in one or less quintile change (98.7%). Only mean daily fruit and vegetable food group intakes were higher in women than in men (278 vs 212 and 284 vs 255 g, respectively). Quintile changes were evident for all nutrients, with the exception of alcohol, when text matching was not executed; however, only the cereals food group was affected. Conclusions FETA produces similar nutrient and food group values to the previously validated CAFe but has the advantages of being open source, cross-platform and complete with a data-entry form directly compatible with the software. The tool will facilitate research using the EPIC-Norfolk FFQ, and can be customised for different study populations.
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关键词
research methods,biomedical research,bioinformatics
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